Utilizing artificial intelligence to make a prediction about an entity based on user sentiment and transaction history

1. A device, comprising: one or more memories; a communication interface to establish communication with devices in an environment; a prediction component to generate a future stock price associated with an entity; and one or more processors, communicatively coupled to the one or more memories, to: receive comment information, via the communication interface, associated with a plurality of users, the comment information including comments provided by the plurality of users, about the entity, via one or more social media sources; generate a plurality of interim scores associated with the entity via artificial intelligence based upon the comment information, the plurality of interim scores including at least two of: a necessity score, an abstract score, an ethics score, an industry score, a demand for service score, a supply for service score, a vendor score, an innovation score, an adaptability score, or an execution score, receive transaction information associated with the plurality of users, the transaction information including financial transactions of one or more of the plurality of users with the entity; determine correlations between the plurality of interim scores associated with the comment information and the transaction information, the correlations between the plurality of interim scores associated with the comment information and the transaction information being determined by using at least one of: a correlation clustering method, a Pearson's product-moment coefficient method, an Anscombe's quartet method, or a Spearman's rank-correlation coefficient method, the correlations between the plurality of interim scores associated with the comment information and the transaction information providing a plurality of weights to the comment information, the providing the plurality of weights to the comment information generating weighted comment information; generate a prediction about the future stock price of the entity based on the weighted comment information, the transaction information, and the correlations between the comment information and the transaction information; store the weighted comment information, the transaction information, and prediction information in a relational database to reduce redundancy, the relational database being organized in columns and tables via a data normalization method; provide the prediction about the future stock price of the entity for display; and cause an action to be taken based on the prediction about the future stock price of the entity, the action including one or more of: automatically providing, to a client device, a notification indicating the future stock price of the entity, automatically sending an instruction to a server to buy or sell a stock associated with the entity, or automatically causing a calculation of a future value of a financial portfolio to be generated.

2. The device of claim 1 , where the comment information includes one or more of: complaint information relating to the entity, the complaint information including information indicating: a negative statement about the entity, a switch from the entity to another entity, or an invalidation of a product or service of the entity, opinion information relating to the entity, the opinion information including information indicating: a feeling about the entity, an opinion about the entity, or an expression that the entity lacks innovation, or prediction information relating to the entity, the prediction information including information indicating: a prediction about the entity, or a prospective statement about the entity.

3. The device of claim 1 , where the one or more processors are further to: receive historical information associated with the entity; generate the plurality of interim scores for the comment information based on the historical information; and generate the prediction about the future stock price of the entity based on the plurality of interim scores and the correlations between the comment information and the transaction information.

4. The device of claim 3 , where the one or more processors are further to: generate a combined score based on the plurality of interim scores; and generate the prediction about the future stock price of the entity based on the combined score and the correlations between the comment information and the transaction information.

5. The device of claim 3 , where the one or more processors are further to: apply the plurality of weights to the plurality of interim scores to generate a plurality of weighted interim scores; and generate the prediction about the future stock price of the entity based on the plurality of weighted interim scores.

6. The device of claim 1 , where the prediction about the future stock price of the entity includes a prediction about a stock price of the entity at a particular time in the future.

7. A method, comprising: receiving, by a device, complaint information, opinion information, and prediction information associated with a plurality of users, the complaint information, the opinion information, and the prediction information being received from one or more social media sources, and the complaint information, the opinion information, and the prediction information relating to an entity; generating, by the device, a plurality of interim scores associated with the entity via artificial intelligence based upon the complaint information, the plurality of interim scores including at least two of: a necessity score, an abstract score, an ethics score, an industry score, a demand for service score, a supply for service score, a vendor score, an innovation score, an adaptability score, or an execution score; receiving, by the device, transaction information associated with one or more of the plurality of users, the transaction information being received from: a plurality of financial institutions, or the one or more of the plurality of users, and the transaction information relating to the entity; determining, by the device, correlations between the plurality of interim scores associated with the transaction information and the complaint information, the opinion information, and the prediction information, the correlations between the plurality of interim scores associated with the complaint information and the transaction information being determined by using at least one of: a correlation clustering method, a Pearson's product-moment coefficient method, an Anscombe's quartet method, or a Spearman's rank-correlation coefficient method, the correlations between the plurality of interim scores associated with transaction information and the complaint information, the opinion information, and the prediction information providing a plurality of weights to the complaint information, the opinion information, and the prediction information; generating, by the device, a prediction about a future stock price of the entity based on the complaint information, the opinion information, the prediction information, the transaction information, and the correlations between the transaction information and the complaint information, the opinion information, and the prediction information; storing, by the device, the complaint information, the transaction information, and prediction information in a relational database to reduce redundancy, the relational database being organized in columns and tables via a data normalization method; providing, by the device, the prediction about the future stock price of the entity for display; and causing, by the device, an action to be taken based on the prediction about the future stock price of the entity, the action including one or more of: automatically providing, to a client device, a notification indicating the future stock price of the entity, automatically sending an instruction to a server to buy or sell a stock associated with the entity, or automatically causing a calculation of a future value of a financial portfolio to be generated.

8. The method of claim 7 , where the complaint information includes information indicating: a negative statement about the entity, a switch from the entity to another entity, or an invalidation of a product or service of the entity, the opinion information includes information indicating: a feeling about the entity, an opinion about the entity, or an expression that the entity lacks innovation, and the prediction information includes information indicating: a prediction about the entity, or a prospective statement about the entity.

9. The method of claim 7 , further comprising: receiving historical information associated with the entity; generating the plurality of interim scores for the complaint information, the opinion information, and the prediction information based on the historical information; and generating the prediction about the future stock price of the entity based on the plurality of interim scores and the correlations between the transaction information and the complaint information, the opinion information, and the prediction information.

10. The method of claim 9 , further comprising: generating a combined score based on the plurality of interim scores; and generating the prediction about the future stock price of the entity based on the combined score and the correlations between the transaction information and the complaint information, the opinion information, and the prediction information.

11. The method of claim 9 , further comprising: applying the plurality of weights to the plurality of interim scores to generate a plurality of weighted interim scores; and generating the prediction about the future stock price of the entity based on the plurality of weighted interim scores.

12. The method of claim 7 , further comprising: generating, based on the complaint information, the opinion information, the prediction information, the transaction information, and the correlations between the transaction information and the complaint information, the opinion information, and the prediction information, a prediction about one or more of: a stock price of the entity, a value of the entity, a price to book ratio of the entity, a price to earnings ratio of the entity, a price to earnings growth ratio of the entity, a dividend yield of the entity, an earnings per share ratio of the entity, a growth rate of the entity, a return on invested capital of the entity, a return on assets of the entity, or a price to sales ratio of the entity.

13. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors of a device, cause the one or more processors to: receive historical information associated with an entity; receive comment information associated with a plurality of users, the comment information relating to the entity; receive transaction information associated with one or more of the plurality of users, the transaction information relating to the entity; utilize artificial intelligence to calculate a plurality of interim scores for the entity based on the historical information and the comment information, the plurality of interim scores including at least two of: a necessity score, an abstract score, an ethics score, an industry score, a demand for service score, a supply for service score, a vendor score, an innovation score, an adaptability score, or an execution score; determine correlations between the plurality of interim scores associated with the comment information and the transaction information, the correlations between the plurality of interim scores associated with the comment information and the transaction information being determined by using at least one of: a correlation clustering method, a Pearson's product-moment coefficient method, an Anscombe's quartet method, or a Spearman's rank-correlation coefficient method; apply weights to the plurality of interim scores, based on the correlations between the plurality of interim scores and the transaction information, and to generate a plurality of weighted interim scores; generate a prediction about a future stock price of the entity based on the plurality of weighted interim scores; store the comment information, the transaction information, and prediction information in a relational database to reduce redundancy, the relational database being organized in columns and tables via a data normalization method; provide the prediction about the future stock price of the entity for display; and cause an action to be taken based on the prediction about the future stock price of the entity, the action including one or more of: automatically providing, to a client device, a notification indicating the future stock price of the entity, automatically sending an instruction to a server to buy or sell a stock associated with the entity, or automatically causing a calculation of a future value of a financial portfolio to be generated.

14. The non-transitory computer-readable medium of claim 13 , where the comment information includes one or more of: complaint information relating to the entity, the complaint information including information indicating: a negative statement about the entity, a switch from the entity to another entity, or an invalidation of a product or service of the entity, opinion information relating to the entity, the opinion information including information indicating: a feeling about the entity, an opinion about the entity, or an expression that the entity lacks innovation, or prediction information relating to the entity, the prediction information including information indicating: a prediction about the entity, or a prospective statement about the entity.

15. The non-transitory computer-readable medium of claim 13 , where the instructions further comprise: one or more instructions that, when executed by the one or more processors, cause the one or more processors to: generate a combined score based on the plurality of weighted interim scores; and generate the prediction about the future stock price of the entity based on the combined score.

16. The non-transitory computer-readable medium of claim 13 , where the entity includes a company associated with a stock.

17. The non-transitory computer-readable medium of claim 16 , where the prediction about the future stock price of the entity includes a prediction about a stock price of the entity at a particular time in the future.

18. The device of claim 1 , where the one or more processors are further to: automatically provide, based on the prediction about the future stock price of the entity, a request for permission to buy or sell a stock associated with the entity.

19. The method of claim 7 , further comprising: automatically sell, based on the prediction about the future stock price of the entity, a stock associated with the entity.

20. The non-transitory computer-readable medium of claim 13 , where the instructions further comprise: one or more instructions that, when executed by the one or more processors, further cause the one or more processors to: automatically sell, based on the prediction about the future stock price of the entity, a stock associated with the entity.